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- W292013505 abstract "Abstract This research focuses on daylight assessment in office buildings with different atrium types, proportions and roof aperture designs. The goal is to assess and optimize atrium type and proportions to improve energy efficiency of atrium buildings. This paper investigates daylight metrics in central, attached and semi-enclosed atrium types with different proportions and roof aperture designs, such as monitor and horizontal skylight. Daylight performance is measured based on the proportions of an atrium that are defined by Well Index (WI), used to characterize atria. Climate-Based Daylight Modeling (CBDM) is applied as the assessment strategy with U.S Climate Zone 3 as the climatic setting. Spatial Daylight Autonomy (sDA) and Annual Solar Exposure (ASE) are adopted as the dynamic daylight metrics to compare the results. This study also validates DIVA for Rhino as the simulation tool by comparing daylight results of the computer simulation with the same scale-model. This research applies both scale-model and computer simulation methods to assess daylight and energy performance in atrium buildings based on Well Index. This paper then employs DIVA simulation tool to assess daylight performance based on the Well Index. The results demonstrate that Well Index is a reliable indicator to characterize atrium proportion and confirm that Well Index works with (CBDM). Having assessed the impact of design parameters, such as climate, building thickness, material reflectance, material transmittance, furniture and monitor roof glazing height, the study potentially provides architects with an atrium design database for U.S. Climate Zone 3. This database compares daylight metrics for Well Index of 0.5, 1 and 2 in central, attached and semi-enclosed atrium types using different roof aperture designs." @default.
- W292013505 created "2016-06-24" @default.
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- W292013505 date "2015-09-01" @default.
- W292013505 modified "2023-10-12" @default.
- W292013505 title "Assessing daylight performance in atrium buildings by using Climate Based Daylight Modeling" @default.
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- W292013505 doi "https://doi.org/10.1016/j.solener.2015.05.011" @default.
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